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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26610
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dc.contributor.authorChen, X-
dc.contributor.authorYang, R-
dc.contributor.authorXue, Y-
dc.contributor.authorHuang, M-
dc.contributor.authorFerrero, R-
dc.contributor.authorWang, Z-
dc.date.accessioned2023-06-06T13:40:35Z-
dc.date.available2023-06-06T13:40:35Z-
dc.date.issued2023-02-13-
dc.identifierORCID iDs: Xiaohan Chen https://orcid.org/0000-0001-6462-4216; Rui Yang https://orcid.org/0000-0002-5634-5476; Yihao Xue https://orcid.org/0000-0002-3310-4864; Mengjie Huang https://orcid.org/0000-0001-8163-8679; Roberto Ferrero https://orcid.org/0000-0001-7820-9021; Zidong Wang https://orcid.org/0000-0002-9576-7401.-
dc.identifier3508221-
dc.identifier.citationChen, X. et al. (2023) 'Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016', IEEE Transactions on Instrumentation and Measurement, 72, pp. 1 - 21. doi: /10.1109/TIM.2023.3244237.en_US
dc.identifier.issn0018-9456-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/26610-
dc.description.sponsorship10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61603223); Jiangsu Provincial Qinglan Project; 10.13039/501100018556-Suzhou Science and Technology Program (Grant Number: SYG202106); Research Development Fund of Xi’an Jiaotong–Liverpool University (XJTLU) (Grant Number: RDF-18-02-30 and RDF-20-01-18); Key Program Special Fund in XJTLU (Grant Number: KSF-E-34); 10.13039/501100010023-Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant Number: 20KJB520034).en_US
dc.format.extent1 - 21-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.rightsCopyright © 2023 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works by sending a request to pubs-permissions@ieee.org. For more information, see https://www.ieee.org/publications/rights/rights-policies.html-
dc.rights.urihttps://www.ieee.org/publications/rights/rights-policies.html-
dc.subjectbearing faulten_US
dc.subjectdeep transfer learningen_US
dc.subjectfault diagnosisen_US
dc.titleDeep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016en_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1109/TIM.2023.3244237-
dc.relation.isPartOfIEEE Transactions on Instrumentation and Measurement-
pubs.publication-statusPublished-
pubs.volume72-
dc.identifier.eissn1557-9662-
dc.rights.holderInstitute of Electrical and Electronics Engineers (IEEE)-
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